polars

A fast DataFrame library implemented in Rust with a Python API.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is polars?

Polars is a high-performance DataFrame library written in Rust that provides a Python API for efficient data manipulation and analysis. It is designed to handle large datasets quickly, making it ideal for data-intensive applications.

Key differentiator

Polars stands out as a high-performance DataFrame library written in Rust, offering efficient memory management and fast operations, making it ideal for developers who need speed and efficiency.

Capability profile

Strength Radar

High-performance…Efficient memory…Support for lazy…Wide range of op…

Honest assessment

Strengths & Weaknesses

↑ Strengths

High-performance data manipulation and analysis

Efficient memory management

Support for lazy evaluation to optimize performance

Wide range of operations including filtering, grouping, and joining

Fit analysis

Who is it for?

✓ Best for

Developers working with Python who need high-performance DataFrame operations

Projects requiring efficient memory usage and fast data manipulation

Applications that process large volumes of data in real-time

✕ Not a fit for

Teams needing a web-based UI for data analysis (polars is a library)

Projects where the primary language is not Python or Rust

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with polars

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →